Methods for combining decoder side motion vector refinement with wrap-around motion compensation

ABSTRACT

The present disclosure provides systems and methods for processing video data. According to certain disclosed embodiments, a method includes: performing a decoder side motion vector refinement (DMVR) process to generate a bi-predicted signal, wherein performing the DMVR process comprises: determining a refined motion vector for a target coding unit, without using wrap-around motion compensation; determining whether the wrap-around motion compensation is enabled; and in response to a determination that the wrap-around motion compensation is enabled, generating, based on the refined motion vector, a bi-predicted signal using the wrap-around motion compensation.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present disclosure claims priority to and the benefits of priorityto U.S. Provisional Patent Application No. 62/980,974, filed on Feb. 24,2020. The provisional application is incorporated herein by reference inits entirety.

TECHNICAL FIELD

The present disclosure generally relates to video processing, and moreparticularly, to methods and apparatuses for simplifying decoder sidemotion vector refinement (DMVR) process when it is combined withwrap-around motion compensation.

BACKGROUND

A video is a set of static pictures (or “frames”) capturing the visualinformation. To reduce the storage memory and the transmissionbandwidth, a video can be compressed before storage or transmission anddecompressed before display. The compression process is usually referredto as encoding and the decompression process is usually referred to asdecoding. There are various video coding formats which use standardizedvideo coding technologies, most commonly based on prediction, transform,quantization, entropy coding and in-loop filtering. The video codingstandards, such as the High Efficiency Video Coding (e.g., HEVC/H.265)standard, the Versatile Video Coding (e.g., VVC/H.266) standard, and AVSstandards, specifying the specific video coding formats, are developedby standardization organizations. With more and more advanced videocoding technologies being adopted in the video standards, the codingefficiency of the new video coding standards get higher and higher.

SUMMARY OF THE DISCLOSURE

Embodiments of the present disclosure provide a method for simplifyingdecoder side motion vector refinement process when it is combined withwrap-around motion compensation. In some exemplary embodiments, themethod includes: performing a DMVR process to generate a bi-predictedsignal, wherein performing the DMVR process comprises: determining arefined motion vector for a target coding unit, without usingwrap-around motion compensation; determining whether the wrap-aroundmotion compensation is enabled; and in response to a determination thatthe wrap-around motion compensation is enabled, generating, based on therefined motion vector, a bi-predicted signal using the wrap-aroundmotion compensation.

Embodiments of the present disclosure further provide a system forperforming video data processing. The system comprises: a memory storinga set of instructions; and a processor configured to execute the set ofinstructions to cause the system to perform: performing a DMVR processto generate a bi-predicted signal, wherein performing the DMVR processcomprises: determining a refined motion vector for a target coding unit,without using wrap-around motion compensation; determining whether thewrap-around motion compensation is enabled; and in response to adetermination that the wrap-around motion compensation is enabled,generating, based on the refined motion vector, a bi-predicted signalusing the wrap-around motion compensation.

Embodiments of the present disclosure further provide a non-transitorycomputer readable medium that stores a set of instructions that isexecutable by one or more processors of an apparatus to cause theapparatus to initiate a method for performing video data processing. Themethod comprises: performing a DMVR process to generate a bi-predictedsignal, wherein performing the DMVR process comprises: determining arefined motion vector for a target coding unit, without usingwrap-around motion compensation; determining whether the wrap-aroundmotion compensation is enabled; and in response to a determination thatthe wrap-around motion compensation is enabled, generating, based on therefined motion vector, a bi-predicted signal using the wrap-aroundmotion compensation.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments and various aspects of the present disclosure areillustrated in the following detailed description and the accompanyingfigures. Various features shown in the figures are not drawn to scale.

FIG. 1 shows structures of an example video sequence, according to someembodiments of the present disclosure.

FIG. 2A shows a schematic of an example encoding process, according tosome embodiments of the present disclosure.

FIG. 2B shows a schematic of another example encoding process, accordingto some embodiments of the present disclosure.

FIG. 3A shows a schematic of an example decoding process, according tosome embodiments of the present disclosure.

FIG. 3B shows a schematic of another example decoding process, accordingto some embodiments of the present disclosure.

FIG. 4 shows a block diagram of an example apparatus for encoding ordecoding a video, according to some embodiments of the presentdisclosure.

FIG. 5A shows a schematic of an example blending operation forgenerating reconstructed equirectangular projections, according to someembodiments of the present disclosure.

FIG. 5B shows schematic of an example cropping operation for generatingreconstructed equirectangular projections, according to some embodimentsof the present disclosure.

FIG. 6A shows a schematic of an example horizontal wrap-around motioncompensation process for equirectangular projections, according to someembodiments of the present disclosure.

FIG. 6B shows a schematic of an example horizontal wrap-around motioncompensation process for padded equirectangular projections, accordingto some embodiments of the present disclosure.

FIG. 7 shows a schematic of an example bilateral-matching based decodingside motion vector refinement, according to some embodiments of thepresent disclosure.

FIG. 8 shows a schematic of an example decoding side motion vectorrefinement in combination with a wrap-around motion compensation,according to some embodiments of the present disclosure.

FIG. 9 shows semantics of an example improved fractional sample bilinearinterpolation process, according to some embodiments of the presentdisclosure.

FIG. 10 shows a flowchart of an example decoding side motion vectorrefinement in combination with a wrap-around motion compensation,according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments, examplesof which are illustrated in the accompanying drawings. The followingdescription refers to the accompanying drawings in which the samenumbers in different drawings represent the same or similar elementsunless otherwise represented. The implementations set forth in thefollowing description of exemplary embodiments do not represent allimplementations consistent with the present disclosure. Instead, theyare merely examples of apparatuses and methods consistent with aspectsrelated to the present disclosure as recited in the appended claims.Particular aspects of the present disclosure are described in greaterdetail below. The terms and definitions provided herein control, if inconflict with terms and/or definitions incorporated by reference.

The Joint Video Experts Team (JVET) of the ITU-T Video Coding ExpertGroup (ITU-T VCEG) and the ISO/IEC Moving Picture Expert Group (ISO/IECMPEG) is currently developing the Versatile Video Coding (VVC/H.266)standard. The VVC standard is aimed at doubling the compressionefficiency of its predecessor, the High Efficiency Video Coding(HEVC/H.265) standard. In other words, VVC's goal is to achieve the samesubjective quality as HEVC/H.265 using half the bandwidth.

In order to achieve the same subjective quality as HEVC/H.265 using halfthe bandwidth, the Joint Video Experts Team (“JVET”) has been developingtechnologies beyond HEVC using the joint exploration model (“JEM”)reference software. As coding technologies were incorporated into theJEM, the JEM achieved substantially higher coding performance than HEVC.The VCEG and MPEG have also formally started the development of a nextgeneration video compression standard beyond HEVC.

The VVC standard has been developed recently and continues to includemore coding technologies that provide better compression performance.VVC is based on the same hybrid video coding system that has been usedin modern video compression standards such as HEVC, H.264/AVC, MPEG2,H.263, etc.

A video is a set of static pictures (or frames) arranged in a temporalsequence to store visual information. A video capture device (e.g., acamera) can be used to capture and store those pictures in a temporalsequence, and a video playback device (e.g., a television, a computer, asmartphone, a tablet computer, a video player, or any end-user terminalwith a function of display) can be used to display such pictures in thetemporal sequence. Also, in some applications, a video capturing devicecan transmit the captured video to the video playback device (e.g., acomputer with a monitor) in real-time, such as for surveillance,conferencing, or live broadcasting.

To reduce the storage space and the transmission bandwidth needed bysuch applications, the video can be compressed. For example, the videocan be compressed before storage and transmission and decompressedbefore the display. The compression and decompression can be implementedby software executed by a processor (e.g., a processor of a genericcomputer) or specialized hardware. The module or circuitry forcompression is generally referred to as an “encoder,” and the module orcircuitry for decompression is generally referred to as a “decoder.” Theencoder and the decoder can be collectively referred to as a “codec.”The encoder and the decoder can be implemented as any of a variety ofsuitable hardware, software, or a combination thereof. For example, thehardware implementation of the encoder and the decoder can includecircuitry, such as one or more microprocessors, digital signalprocessors (“DSPs”), application-specific integrated circuits (“ASICs”),field-programmable gate arrays (“FPGAs”), discrete logic, or anycombinations thereof. The software implementation of the encoder and thedecoder can include program codes, computer-executable instructions,firmware, or any suitable computer-implemented algorithm or processfixed in a computer-readable medium. Video compression and decompressioncan be implemented by various algorithms or standards, such as MPEG-1,MPEG-2, MPEG-4, H.26x series, or the like. In some applications, thecodec can decompress the video from a first coding standard andre-compress the decompressed video using a second coding standard, inwhich case the codec can be referred to as a “transcoder.”

The video encoding process can identify and keep useful information thatcan be used to reconstruct a picture. If information that wasdisregarded in the video encoding process cannot be fully reconstructed,the encoding process can be referred to as “lossy.” Otherwise, it can bereferred to as “lossless.” Most encoding processes are lossy, which is atradeoff to reduce the needed storage space and the transmissionbandwidth.

In many cases, the useful information of a picture being encoded(referred to as a “current picture”) can include changes with respect toa reference picture (e.g., a picture previously encoded orreconstructed). Such changes can include position changes, luminositychanges, or color changes of the pixels. Position changes of a group ofpixels that represent an object can reflect the motion of the objectbetween the reference picture and the current picture.

A picture coded without referencing another picture (i.e., it is its ownreference picture) is referred to as an “I-picture.” A picture isreferred to as a “P-picture” if some or all blocks (e.g., blocks thatgenerally refer to portions of the video picture) in the picture arepredicted using intra prediction or inter prediction with one referencepicture (e.g., uni-prediction). A picture is referred to as a“B-picture” if at least one block in it is predicted with two referencepictures (e.g., bi-prediction).

FIG. 1 shows structures of an example video sequence, according to someembodiments of the present disclosure. As shown in FIG. 1, videosequence 100 can be a live video or a video having been captured andarchived. Video 100 can be a real-life video, a computer-generated video(e.g., computer game video), or a combination thereof (e.g., a real-lifevideo with augmented-reality effects). Video sequence 100 can beinputted from a video capture device (e.g., a camera), a video archive(e.g., a video file stored in a storage device) containing previouslycaptured video, or a video feed interface (e.g., a video broadcasttransceiver) to receive video from a video content provider.

As shown in FIG. 1, video sequence 100 can include a series of picturesarranged temporally along a timeline, including pictures 102, 104, 106,and 108. Pictures 102-106 are continuous, and there are more picturesbetween pictures 106 and 108. In FIG. 1, picture 102 is an I-picture,the reference picture of which is picture 102 itself. Picture 104 is aP-picture, the reference picture of which is picture 102, as indicatedby the arrow. Picture 106 is a B-picture, the reference pictures ofwhich are pictures 104 and 108, as indicated by the arrows. In someembodiments, the reference picture of a picture (e.g., picture 104) canbe not immediately preceding or following the picture. For example, thereference picture of picture 104 can be a picture preceding picture 102.It should be noted that the reference pictures of pictures 102-106 areonly examples, and the present disclosure does not limit embodiments ofthe reference pictures as the examples shown in FIG. 1.

Typically, video codecs do not encode or decode an entire picture at onetime due to the computing complexity of such tasks. Rather, they cansplit the picture into basic segments, and encode or decode the picturesegment by segment. Such basic segments are referred to as basicprocessing units (“BPUs”) in the present disclosure. For example,structure 110 in FIG. 1 shows an example structure of a picture of videosequence 100 (e.g., any of pictures 102-108). In structure 110, apicture is divided into 4×4 basic processing units, the boundaries ofwhich are shown as dash lines. In some embodiments, the basic processingunits can be referred to as “macroblocks” in some video coding standards(e.g., MPEG family, H.261, H.263, or H.264/AVC), or as “coding treeunits” (“CTUs”) in some other video coding standards (e.g., H.265/HEVCor H.266NVC). The basic processing units can have variable sizes in apicture, such as 128×128, 64×64, 32×32, 16×16, 4×8, 16×32, or anyarbitrary shape and size of pixels. The sizes and shapes of the basicprocessing units can be selected for a picture based on the balance ofcoding efficiency and levels of details to be kept in the basicprocessing unit.

The basic processing units can be logical units, which can include agroup of different types of video data stored in a computer memory(e.g., in a video frame buffer). For example, a basic processing unit ofa color picture can include a luma component (Y) representing achromaticbrightness information, one or more chroma components (e.g., Cb and Cr)representing color information, and associated syntax elements, in whichthe luma and chroma components can have the same size of the basicprocessing unit. The luma and chroma components can be referred to as“coding tree blocks” (“CTBs”) in some video coding standards (e.g.,H.265/HEVC or H.266/VVC). Any operation performed to a basic processingunit can be repeatedly performed to each of its luma and chromacomponents.

Video coding has multiple stages of operations, examples of which areshown in FIGS. 2A-2B and FIGS. 3A-3B. For each stage, the size of thebasic processing units can still be too large for processing, and thuscan be further divided into segments referred to as “basic processingsub-units” in the present disclosure. In some embodiments, the basicprocessing sub-units can be referred to as “blocks” in some video codingstandards (e.g., MPEG family, H.261, H.263, or H.264/AVC), or as “codingunits” (“CUs”) in some other video coding standards (e.g., H.265/HEVC orH.266/VVC). A basic processing sub-unit can have the same or smallersize than the basic processing unit. Similar to the basic processingunits, basic processing sub-units are also logical units, which caninclude a group of different types of video data (e.g., Y, Cb, Cr, andassociated syntax elements) stored in a computer memory (e.g., in avideo frame buffer). Any operation performed to a basic processingsub-unit can be repeatedly performed to each of its luma and chromacomponents. It should be noted that such division can be performed tofurther levels depending on processing needs. It should also be notedthat different stages can divide the basic processing units usingdifferent schemes.

For example, at a mode decision stage (an example of which is shown inFIG. 2B), the encoder can decide what prediction mode (e.g.,intra-picture prediction or inter-picture prediction) to use for a basicprocessing unit, which can be too large to make such a decision. Theencoder can split the basic processing unit into multiple basicprocessing sub-units (e.g., CUs as in H.265/HEVC or H.266NVC), anddecide a prediction type for each individual basic processing sub-unit.

For another example, at a prediction stage (an example of which is shownin FIGS. 2A-2B), the encoder can perform prediction operation at thelevel of basic processing sub-units (e.g., CUs). However, in some cases,a basic processing sub-unit can still be too large to process. Theencoder can further split the basic processing sub-unit into smallersegments (e.g., referred to as “prediction blocks” or “PBs” inH.265/HEVC or H.266/VVC), at the level of which the prediction operationcan be performed.

For another example, at a transform stage (an example of which is shownin FIGS. 2A-2B), the encoder can perform a transform operation forresidual basic processing sub-units (e.g., CUs). However, in some cases,a basic processing sub-unit can still be too large to process. Theencoder can further split the basic processing sub-unit into smallersegments (e.g., referred to as “transform blocks” or “TBs” in H.265/HEVCor H.266/VVC), at the level of which the transform operation can beperformed. It should be noted that the division schemes of the samebasic processing sub-unit can be different at the prediction stage andthe transform stage. For example, in H.265/HEVC or H.266/VVC, theprediction blocks and transform blocks of the same CU can have differentsizes and numbers.

In structure 110 of FIG. 1, basic processing unit 112 is further dividedinto 3×3 basic processing sub-units, the boundaries of which are shownas dotted lines. Different basic processing units of the same picturecan be divided into basic processing sub-units in different schemes.

In some implementations, to provide the capability of parallelprocessing and error resilience to video encoding and decoding, apicture can be divided into regions for processing, such that, for aregion of the picture, the encoding or decoding process can depend on noinformation from any other region of the picture. In other words, eachregion of the picture can be processed independently. By doing so, thecodec can process different regions of a picture in parallel, thusincreasing the coding efficiency. Also, when data of a region iscorrupted in the processing or lost in network transmission, the codeccan correctly encode or decode other regions of the same picture withoutreliance on the corrupted or lost data, thus providing the capability oferror resilience. In some video coding standards, a picture can bedivided into different types of regions. For example, H.265/HEVC andH.266/VVC provide two types of regions: “slices” and “tiles.” It shouldalso be noted that different pictures of video sequence 100 can havedifferent partition schemes for dividing a picture into regions.

For example, in FIG. 1, structure 110 is divided into three regions 114,116, and 118, the boundaries of which are shown as solid lines insidestructure 110. Region 114 includes four basic processing units. Each ofregions 116 and 118 includes six basic processing units. It should benoted that the basic processing units, basic processing sub-units, andregions of structure 110 in FIG. 1 are only examples, and the presentdisclosure does not limit embodiments thereof.

FIG. 2A shows a schematic of an example encoding process, according tosome embodiments of the present disclosure. For example, encodingprocess 200A shown in FIG. 2A can be performed by an encoder. As shownin FIG. 2A, the encoder can encode video sequence 202 into videobitstream 228 according to process 200A. Similar to video sequence 100in FIG. 1, video sequence 202 can include a set of pictures (referred toas “original pictures”) arranged in a temporal order. Similar tostructure 110 in FIG. 1, each original picture of video sequence 202 canbe divided by the encoder into basic processing units, basic processingsub-units, or regions for processing. In some embodiments, the encodercan perform process 200A at the level of basic processing units for eachoriginal picture of video sequence 202. For example, the encoder canperform process 200A in an iterative manner, in which the encoder canencode a basic processing unit in one iteration of process 200A. In someembodiments, the encoder can perform process 200A in parallel forregions (e.g., regions 114-118) of each original picture of videosequence 202.

In FIG. 2A, the encoder can feed a basic processing unit (referred to asan “original BPU”) of an original picture of video sequence 202 toprediction stage 204 to generate prediction data 206 and predicted BPU208. The encoder can subtract predicted BPU 208 from the original BPU togenerate residual BPU 210. The encoder can feed residual BPU 210 totransform stage 212 and quantization stage 214 to generate quantizedtransform coefficients 216. The encoder can feed prediction data 206 andquantized transform coefficients 216 to binary coding stage 226 togenerate video bitstream 228. Components 202, 204, 206, 208, 210, 212,214, 216, 226, and 228 can be referred to as a “forward path.” Duringprocess 200A, after quantization stage 214, the encoder can feedquantized transform coefficients 216 to inverse quantization stage 218and inverse transform stage 220 to generate reconstructed residual BPU222. The encoder can add reconstructed residual BPU 222 to predicted BPU208 to generate prediction reference 224, which is used in predictionstage 204 for the next iteration of process 200A. Components 218, 220,222, and 224 of process 200A can be referred to as a “reconstructionpath.” The reconstruction path can be used to ensure that both theencoder and the decoder use the same reference data for prediction.

The encoder can perform process 200A iteratively to encode each originalBPU of the original picture (in the forward path) and generate predictedreference 224 for encoding the next original BPU of the original picture(in the reconstruction path). After encoding all original BPUs of theoriginal picture, the encoder can proceed to encode the next picture invideo sequence 202.

Referring to process 200A, the encoder can receive video sequence 202generated by a video capturing device (e.g., a camera). The term“receive” used herein can refer to receiving, inputting, acquiring,retrieving, obtaining, reading, accessing, or any action in any mannerfor inputting data.

At prediction stage 204, at a current iteration, the encoder can receivean original BPU and prediction reference 224, and perform a predictionoperation to generate prediction data 206 and predicted BPU 208.Prediction reference 224 can be generated from the reconstruction pathof the previous iteration of process 200A. The purpose of predictionstage 204 is to reduce information redundancy by extracting predictiondata 206 that can be used to reconstruct the original BPU as predictedBPU 208 from prediction data 206 and prediction reference 224.

Ideally, predicted BPU 208 can be identical to the original BPU.However, due to non-ideal prediction and reconstruction operations,predicted BPU 208 is generally slightly different from the original BPU.For recording such differences, after generating predicted BPU 208, theencoder can subtract it from the original BPU to generate residual BPU210. For example, the encoder can subtract values (e.g., greyscalevalues or RGB values) of pixels of predicted BPU 208 from values ofcorresponding pixels of the original BPU. Each pixel of residual BPU 210can have a residual value as a result of such subtraction between thecorresponding pixels of the original BPU and predicted BPU 208. Comparedwith the original BPU, prediction data 206 and residual BPU 210 can havefewer bits, but they can be used to reconstruct the original BPU withoutsignificant quality deterioration. Thus, the original BPU is compressed.

To further compress residual BPU 210, at transform stage 212, theencoder can reduce spatial redundancy of residual BPU 210 by decomposingit into a set of two-dimensional “base patterns,” each base patternbeing associated with a “transform coefficient.” The base patterns canhave the same size (e.g., the size of residual BPU 210). Each basepattern can represent a variation frequency (e.g., frequency ofbrightness variation) component of residual BPU 210. None of the basepatterns can be reproduced from any combinations (e.g., linearcombinations) of any other base patterns. In other words, thedecomposition can decompose variations of residual BPU 210 into afrequency domain. Such a decomposition is analogous to a discreteFourier transform of a function, in which the base patterns areanalogous to the base functions (e.g., trigonometry functions) of thediscrete Fourier transform, and the transform coefficients are analogousto the coefficients associated with the base functions.

Different transform algorithms can use different base patterns. Varioustransform algorithms can be used at transform stage 212, such as, forexample, a discrete cosine transform, a discrete sine transform, or thelike. The transform at transform stage 212 is invertible. That is, theencoder can restore residual BPU 210 by an inverse operation of thetransform (referred to as an “inverse transform”). For example, torestore a pixel of residual BPU 210, the inverse transform can bemultiplying values of corresponding pixels of the base patterns byrespective associated coefficients and adding the products to produce aweighted sum. For a video coding standard, both the encoder and decodercan use the same transform algorithm (thus the same base patterns).Thus, the encoder can record only the transform coefficients, from whichthe decoder can reconstruct residual BPU 210 without receiving the basepatterns from the encoder. Compared with residual BPU 210, the transformcoefficients can have fewer bits, but they can be used to reconstructresidual BPU 210 without significant quality deterioration. Thus,residual BPU 210 is further compressed.

The encoder can further compress the transform coefficients atquantization stage 214. In the transform process, different basepatterns can represent different variation frequencies (e.g., brightnessvariation frequencies). Because human eyes are generally better atrecognizing low-frequency variation, the encoder can disregardinformation of high-frequency variation without causing significantquality deterioration in decoding. For example, at quantization stage214, the encoder can generate quantized transform coefficients 216 bydividing each transform coefficient by an integer value (referred to asa “quantization scale factor”) and rounding the quotient to its nearestinteger. After such an operation, some transform coefficients of thehigh-frequency base patterns can be converted to zero, and the transformcoefficients of the low-frequency base patterns can be converted tosmaller integers. The encoder can disregard the zero-value quantizedtransform coefficients 216, by which the transform coefficients arefurther compressed. The quantization process is also invertible, inwhich quantized transform coefficients 216 can be reconstructed to thetransform coefficients in an inverse operation of the quantization(referred to as “inverse quantization”).

Because the encoder disregards the remainders of such divisions in therounding operation, quantization stage 214 can be lossy. Typically,quantization stage 214 can contribute the most information loss inprocess 200A. The larger the information loss is, the fewer bits thequantized transform coefficients 216 can need. For obtaining differentlevels of information loss, the encoder can use different values of thequantization scale factor or any other parameter of the quantizationprocess.

At binary coding stage 226, the encoder can encode prediction data 206and quantized transform coefficients 216 using a binary codingtechnique, such as, for example, entropy coding, variable length coding,arithmetic coding, Huffman coding, context-adaptive binary arithmeticcoding, or any other lossless or lossy compression algorithm. In someembodiments, besides prediction data 206 and quantized transformcoefficients 216, the encoder can encode other information at binarycoding stage 226, such as, for example, a prediction mode used atprediction stage 204, parameters of the prediction operation, atransform type at transform stage 212, parameters of the quantizationprocess (e.g., quantization scale factors), an encoder control parameter(e.g., a bitrate control parameter), or the like. The encoder can usethe output data of binary coding stage 226 to generate video bitstream228. In some embodiments, video bitstream 228 can be further packetizedfor network transmission.

Referring to the reconstruction path of process 200A, at inversequantization stage 218, the encoder can perform inverse quantization onquantized transform coefficients 216 to generate reconstructed transformcoefficients. At inverse transform stage 220, the encoder can generatereconstructed residual BPU 222 based on the reconstructed transformcoefficients. The encoder can add reconstructed residual BPU 222 topredicted BPU 208 to generate prediction reference 224 that is to beused in the next iteration of process 200A.

It should be noted that other variations of the process 200A can be usedto encode video sequence 202. In some embodiments, stages of process200A can be performed by the encoder in different orders. In someembodiments, one or more stages of process 200A can be combined into asingle stage. In some embodiments, a single stage of process 200A can bedivided into multiple stages. For example, transform stage 212 andquantization stage 214 can be combined into a single stage. In someembodiments, process 200A can include additional stages. In someembodiments, process 200A can omit one or more stages in FIG. 2A.

FIG. 2B shows a schematic of another example encoding process, accordingto some embodiments of the present disclosure. As shown in FIG. 2B,process 200B can be modified from process 200A. For example, process200B can be used by an encoder conforming to a hybrid video codingstandard (e.g., H.26x series). Compared with process 200A, the forwardpath of process 200B additionally includes mode decision stage 230 anddivides prediction stage 204 into spatial prediction stage 2042 andtemporal prediction stage 2044. The reconstruction path of process 200Badditionally includes loop filter stage 232 and buffer 234.

Generally, prediction techniques can be categorized into two types:spatial prediction and temporal prediction. Spatial prediction (e.g., anintra-picture prediction or “intra prediction”) can use pixels from oneor more already coded neighboring BPUs in the same picture to predictthe current BPU. That is, prediction reference 224 in the spatialprediction can include the neighboring BPUs. The spatial prediction canreduce the inherent spatial redundancy of the picture. Temporalprediction (e.g., an inter-picture prediction or “inter prediction”) canuse regions from one or more already coded pictures to predict thecurrent BPU. That is, prediction reference 224 in the temporalprediction can include the coded pictures. The temporal prediction canreduce the inherent temporal redundancy of the pictures.

Referring to process 200B, in the forward path, the encoder performs theprediction operation at spatial prediction stage 2042 and temporalprediction stage 2044. For example, at spatial prediction stage 2042,the encoder can perform the intra prediction. For an original BPU of apicture being encoded, prediction reference 224 can include one or moreneighboring BPUs that have been encoded (in the forward path) andreconstructed (in the reconstructed path) in the same picture. Theencoder can generate predicted BPU 208 by extrapolating the neighboringBPUs. The extrapolation technique can include, for example, a linearextrapolation or interpolation, a polynomial extrapolation orinterpolation, or the like. In some embodiments, the encoder can performthe extrapolation at the pixel level, such as by extrapolating values ofcorresponding pixels for each pixel of predicted BPU 208. Theneighboring BPUs used for extrapolation can be located with respect tothe original BPU from various directions, such as in a verticaldirection (e.g., on top of the original BPU), a horizontal direction(e.g., to the left of the original BPU), a diagonal direction (e.g., tothe down-left, down-right, up-left, or up-right of the original BPU), orany direction defined in the used video coding standard. For the intraprediction, prediction data 206 can include, for example, locations(e.g., coordinates) of the used neighboring BPUs, sizes of the usedneighboring BPUs, parameters of the extrapolation, a direction of theused neighboring BPUs with respect to the original BPU, or the like.

For another example, at temporal prediction stage 2044, the encoder canperform the inter prediction. For an original BPU of a current picture,prediction reference 224 can include one or more pictures (referred toas “reference pictures”) that have been encoded (in the forward path)and reconstructed (in the reconstructed path). In some embodiments, areference picture can be encoded and reconstructed BPU by BPU. Forexample, the encoder can add reconstructed residual BPU 222 to predictedBPU 208 to generate a reconstructed BPU. When all reconstructed BPUs ofthe same picture are generated, the encoder can generate a reconstructedpicture as a reference picture. The encoder can perform an operation of“motion estimation” to search for a matching region in a scope (referredto as a “search window”) of the reference picture. The location of thesearch window in the reference picture can be determined based on thelocation of the original BPU in the current picture. For example, thesearch window can be centered at a location having the same coordinatesin the reference picture as the original BPU in the current picture andcan be extended out for a predetermined distance. When the encoderidentifies (e.g., by using a pel-recursive algorithm, a block-matchingalgorithm, or the like) a region similar to the original BPU in thesearch window, the encoder can determine such a region as the matchingregion. The matching region can have different dimensions (e.g., beingsmaller than, equal to, larger than, or in a different shape) from theoriginal BPU. Because the reference picture and the current picture aretemporally separated in the timeline (e.g., as shown in FIG. 1), it canbe deemed that the matching region “moves” to the location of theoriginal BPU as time goes by. The encoder can record the direction anddistance of such a motion as a “motion vector.” When multiple referencepictures are used (e.g., as picture 106 in FIG. 1), the encoder cansearch for a matching region and determine its associated motion vectorfor each reference picture. In some embodiments, the encoder can assignweights to pixel values of the matching regions of respective matchingreference pictures.

The motion estimation can be used to identify various types of motions,such as, for example, translations, rotations, zooming, or the like. Forinter prediction, prediction data 206 can include, for example,locations (e.g., coordinates) of the matching region, the motion vectorsassociated with the matching region, the number of reference pictures,weights associated with the reference pictures, or the like.

For generating predicted BPU 208, the encoder can perform an operationof “motion compensation.” The motion compensation can be used toreconstruct predicted BPU 208 based on prediction data 206 (e.g., themotion vector) and prediction reference 224. For example, the encodercan move the matching region of the reference picture according to themotion vector, in which the encoder can predict the original BPU of thecurrent picture. When multiple reference pictures are used (e.g., aspicture 106 in FIG. 1), the encoder can move the matching regions of thereference pictures according to the respective motion vectors andaverage pixel values of the matching regions. In some embodiments, ifthe encoder has assigned weights to pixel values of the matching regionsof respective matching reference pictures, the encoder can add aweighted sum of the pixel values of the moved matching regions.

In some embodiments, the inter prediction can be unidirectional orbidirectional. Unidirectional inter predictions can use one or morereference pictures in the same temporal direction with respect to thecurrent picture. For example, picture 104 in FIG. 1 is a unidirectionalinter-predicted picture, in which the reference picture (i.e., picture102) precedes picture 104. Bidirectional inter predictions can use oneor more reference pictures at both temporal directions with respect tothe current picture. For example, picture 106 in FIG. 1 is abidirectional inter-predicted picture, in which the reference pictures(i.e., pictures 104 and 108) are at both temporal directions withrespect to picture 104.

Still referring to the forward path of process 200B, after spatialprediction stage 2042 and temporal prediction stage 2044, at modedecision stage 230, the encoder can select a prediction mode (e.g., oneof the intra prediction or the inter prediction) for the currentiteration of process 200B. For example, the encoder can perform arate-distortion optimization technique, in which the encoder can selecta prediction mode to minimize a value of a cost function depending on abit rate of a candidate prediction mode and distortion of thereconstructed reference picture under the candidate prediction mode.Depending on the selected prediction mode, the encoder can generate thecorresponding predicted BPU 208 and predicted data 206.

In the reconstruction path of process 200B, if intra prediction mode hasbeen selected in the forward path, after generating prediction reference224 (e.g., the current BPU that has been encoded and reconstructed inthe current picture), the encoder can directly feed prediction reference224 to spatial prediction stage 2042 for later usage (e.g., forextrapolation of a next BPU of the current picture). The encoder canfeed prediction reference 224 to loop filter stage 232, at which theencoder can apply a loop filter to prediction reference 224 to reduce oreliminate distortion (e.g., blocking artifacts) introduced during codingof the prediction reference 224. The encoder can apply various loopfilter techniques at loop filter stage 232, such as, for example,deblocking, sample adaptive offsets, adaptive loop filters, or the like.The loop-filtered reference picture can be stored in buffer 234 (or“decoded picture buffer”) for later use (e.g., to be used as aninter-prediction reference picture for a future picture of videosequence 202). The encoder can store one or more reference pictures inbuffer 234 to be used at temporal prediction stage 2044. In someembodiments, the encoder can encode parameters of the loop filter (e.g.,a loop filter strength) at binary coding stage 226, along with quantizedtransform coefficients 216, prediction data 206, and other information.

FIG. 3A shows a schematic of an example decoding process, according tosome embodiments of the present disclosure. As shown in FIG. 3A, process300A can be a decompression process corresponding to the compressionprocess 200A in FIG. 2A. In some embodiments, process 300A can besimilar to the reconstruction path of process 200A. A decoder can decodevideo bitstream 228 into video stream 304 according to process 300A.Video stream 304 can be very similar to video sequence 202. However, dueto the information loss in the compression and decompression process(e.g., quantization stage 214 in FIGS. 2A-2B), generally, video stream304 is not identical to video sequence 202. Similar to processes 200Aand 200B in FIGS. 2A-2B, the decoder can perform process 300A at thelevel of basic processing units (BPUs) for each picture encoded in videobitstream 228. For example, the decoder can perform process 300A in aniterative manner, in which the decoder can decode a basic processingunit in one iteration of process 300A. In some embodiments, the decodercan perform process 300A in parallel for regions (e.g., regions 114-118)of each picture encoded in video bitstream 228.

In FIG. 3A, the decoder can feed a portion of video bitstream 228associated with a basic processing unit (referred to as an “encodedBPU”) of an encoded picture to binary decoding stage 302. At binarydecoding stage 302, the decoder can decode the portion into predictiondata 206 and quantized transform coefficients 216. The decoder can feedquantized transform coefficients 216 to inverse quantization stage 218and inverse transform stage 220 to generate reconstructed residual BPU222. The decoder can feed prediction data 206 to prediction stage 204 togenerate predicted BPU 208. The decoder can add reconstructed residualBPU 222 to predicted BPU 208 to generate predicted reference 224. Insome embodiments, predicted reference 224 can be stored in a buffer(e.g., a decoded picture buffer in a computer memory). The decoder canfeed predicted reference 224 to prediction stage 204 for performing aprediction operation in the next iteration of process 300A.

The decoder can perform process 300A iteratively to decode each encodedBPU of the encoded picture and generate predicted reference 224 forencoding the next encoded BPU of the encoded picture. After decoding allencoded BPUs of the encoded picture, the decoder can output the pictureto video stream 304 for display and proceed to decode the next encodedpicture in video bitstream 228.

At binary decoding stage 302, the decoder can perform an inverseoperation of the binary coding technique used by the encoder (e.g.,entropy coding, variable length coding, arithmetic coding, Huffmancoding, context-adaptive binary arithmetic coding, or any other losslesscompression algorithm). In some embodiments, besides prediction data 206and quantized transform coefficients 216, the decoder can decode otherinformation at binary decoding stage 302, such as, for example, aprediction mode, parameters of the prediction operation, a transformtype, parameters of the quantization process (e.g., quantization scalefactors), an encoder control parameter (e.g., a bitrate controlparameter), or the like. In some embodiments, if video bitstream 228 istransmitted over a network in packets, the decoder can depacketize videobitstream 228 before feeding it to binary decoding stage 302.

FIG. 3B shows a schematic of another example decoding process, accordingto some embodiments of the present disclosure. As shown in FIG. 3B,process 300B can be modified from process 300A. For example, process300B can be used by a decoder conforming to a hybrid video codingstandard (e.g., H.26x series). Compared with process 300A, process 300Badditionally divides prediction stage 204 into spatial prediction stage2042 and temporal prediction stage 2044, and additionally includes loopfilter stage 232 and buffer 234.

In process 300B, for an encoded basic processing unit (referred to as a“current BPU”) of an encoded picture (referred to as a “currentpicture”) that is being decoded, prediction data 206 decoded from binarydecoding stage 302 by the decoder can include various types of data,depending on what prediction mode was used to encode the current BPU bythe encoder. For example, if intra prediction was used by the encoder toencode the current BPU, prediction data 206 can include a predictionmode indicator (e.g., a flag value) indicative of the intra prediction,parameters of the intra prediction operation, or the like. Theparameters of the intra prediction operation can include, for example,locations (e.g., coordinates) of one or more neighboring BPUs used as areference, sizes of the neighboring BPUs, parameters of extrapolation, adirection of the neighboring BPUs with respect to the original BPU, orthe like. For another example, if inter prediction was used by theencoder to encode the current BPU, prediction data 206 can include aprediction mode indicator (e.g., a flag value) indicative of the interprediction, parameters of the inter prediction operation, or the like.The parameters of the inter prediction operation can include, forexample, the number of reference pictures associated with the currentBPU, weights respectively associated with the reference pictures,locations (e.g., coordinates) of one or more matching regions in therespective reference pictures, one or more motion vectors respectivelyassociated with the matching regions, or the like.

Based on the prediction mode indicator, the decoder can decide whetherto perform a spatial prediction (e.g., the intra prediction) at spatialprediction stage 2042 or a temporal prediction (e.g., the interprediction) at temporal prediction stage 2044. The details of performingsuch spatial prediction or temporal prediction are described in FIG. 2Band will not be repeated hereinafter. After performing such spatialprediction or temporal prediction, the decoder can generate predictedBPU 208. The decoder can add predicted BPU 208 and reconstructedresidual BPU 222 to generate prediction reference 224, as described inFIG. 3A.

In process 300B, the decoder can feed predicted reference 224 to spatialprediction stage 2042 or temporal prediction stage 2044 for performing aprediction operation in the next iteration of process 300B. For example,if the current BPU is decoded using the intra prediction at spatialprediction stage 2042, after generating prediction reference 224 (e.g.,the decoded current BPU), the decoder can directly feed predictionreference 224 to spatial prediction stage 2042 for later usage (e.g.,for extrapolation of a next BPU of the current picture). If the currentBPU is decoded using the inter prediction at temporal prediction stage2044, after generating prediction reference 224 (e.g., a referencepicture in which all BPUs have been decoded), the decoder can feedprediction reference 224 to loop filter stage 232 to reduce or eliminatedistortion (e.g., blocking artifacts). The decoder can apply a loopfilter to prediction reference 224, in a way as described in FIG. 2B.The loop-filtered reference picture can be stored in buffer 234 (e.g., adecoded picture buffer in a computer memory) for later use (e.g., to beused as an inter-prediction reference picture for a future encodedpicture of video bitstream 228). The decoder can store one or morereference pictures in buffer 234 to be used at temporal prediction stage2044. In some embodiments, prediction data can further includeparameters of the loop filter (e.g., a loop filter strength). In someembodiments, prediction data includes parameters of the loop filter whenthe prediction mode indicator of prediction data 206 indicates thatinter prediction was used to encode the current BPU.

There can be four types of loop filters. For example, the loop filterscan include a deblocking filter, a sample adaptive offsets (“SAO”)filter, a luma mapping with chroma scaling (“LMCS”) filter, and anadaptive loop filter (“ALF”). The order of applying the four types ofloop filters can be the LMCS filter, the deblocking filter, the SAOfilter, and the ALF. The LMCS filter can include two main components.The first component can be an in-loop mapping of the luma componentbased on adaptive piecewise linear models. The second component can befor the chroma components, and luma-dependent chroma residual scalingcan be applied.

FIG. 4 shows a block diagram of an example apparatus for encoding ordecoding a video, according to some embodiments of the presentdisclosure. As shown in FIG. 4, apparatus 400 can include processor 402.When processor 402 executes instructions described herein, apparatus 400can become a specialized machine for video encoding or decoding.Processor 402 can be any type of circuitry capable of manipulating orprocessing information. For example, processor 402 can include anycombination of any number of a central processing unit (or “CPU”), agraphics processing unit (or “GPU”), a neural processing unit (“NPU”), amicrocontroller unit (“MCU”), an optical processor, a programmable logiccontroller, a microcontroller, a microprocessor, a digital signalprocessor, an intellectual property (IP) core, a Programmable LogicArray (PLA), a Programmable Array Logic (PAL), a Generic Array Logic(GAL), a Complex Programmable Logic Device (CPLD), a Field-ProgrammableGate Array (FPGA), a System On Chip (SoC), an Application-SpecificIntegrated Circuit (ASIC), or the like. In some embodiments, processor402 can also be a set of processors grouped as a single logicalcomponent. For example, as shown in FIG. 4, processor 402 can includemultiple processors, including processor 402 a, processor 402 b, andprocessor 402 n.

Apparatus 400 can also include memory 404 configured to store data(e.g., a set of instructions, computer codes, intermediate data, or thelike). For example, as shown in FIG. 4, the stored data can includeprogram instructions (e.g., program instructions for implementing thestages in processes 200A, 200B, 300A, or 300B) and data for processing(e.g., video sequence 202, video bitstream 228, or video stream 304).Processor 402 can access the program instructions and data forprocessing (e.g., via bus 410), and execute the program instructions toperform an operation or manipulation on the data for processing. Memory404 can include a high-speed random-access storage device or anon-volatile storage device. In some embodiments, memory 404 can includeany combination of any number of a random-access memory (RAM), aread-only memory (ROM), an optical disc, a magnetic disk, a hard drive,a solid-state drive, a flash drive, a security digital (SD) card, amemory stick, a compact flash (CF) card, or the like. Memory 404 canalso be a group of memories (not shown in FIG. 4) grouped as a singlelogical component.

Bus 410 can be a communication device that transfers data betweencomponents inside apparatus 400, such as an internal bus (e.g., aCPU-memory bus), an external bus (e.g., a universal serial bus port, aperipheral component interconnect express port), or the like.

For ease of explanation without causing ambiguity, processor 402 andother data processing circuits are collectively referred to as a “dataprocessing circuit” in this disclosure. The data processing circuit canbe implemented entirely as hardware, or as a combination of software,hardware, or firmware. In addition, the data processing circuit can be asingle independent module or can be combined entirely or partially intoany other component of apparatus 400.

Apparatus 400 can further include network interface 406 to provide wiredor wireless communication with a network (e.g., the Internet, anintranet, a local area network, a mobile communications network, or thelike). In some embodiments, network interface 406 can include anycombination of any number of a network interface controller (NIC), aradio frequency (RF) module, a transponder, a transceiver, a modem, arouter, a gateway, a wired network adapter, a wireless network adapter,a Bluetooth adapter, an infrared adapter, an near-field communication(“NFC”) adapter, a cellular network chip, or the like.

In some embodiments, apparatus 400 can further include peripheralinterface 408 to provide a connection to one or more peripheral devices.As shown in FIG. 4, the peripheral device can include, but is notlimited to, a cursor control device (e.g., a mouse, a touchpad, or atouchscreen), a keyboard, a display (e.g., a cathode-ray tube display, aliquid crystal display, or a light-emitting diode display), a videoinput device (e.g., a camera or an input interface communicativelycoupled to a video archive), or the like.

It should be noted that video codecs (e.g., a codec performing process200A, 200B, 300A, or 300B) can be implemented as any combination of anysoftware or hardware modules in apparatus 400. For example, some or allstages of process 200A, 200B, 300A, or 300B can be implemented as one ormore software modules of apparatus 400, such as program instructionsthat can be loaded into memory 404. For another example, some or allstages of process 200A, 200B, 300A, or 300B can be implemented as one ormore hardware modules of apparatus 400, such as a specialized dataprocessing circuit (e.g., an FPGA, an ASIC, an NPU, or the like).

In the quantization and inverse quantization functional blocks (e.g.,quantization 214 and inverse quantization 218 of FIG. 2A or FIG. 2B,inverse quantization 218 of FIG. 3A or FIG. 3B), a quantizationparameter (QP) is used to determine the amount of quantization (andinverse quantization) applied to the prediction residuals. Initial QPvalues used for coding of a picture or slice can be signaled at the highlevel, for example, using init_qp_minus26 syntax element in the PictureParameter Set (PPS) and using slice_qp_delta syntax element in the sliceheader. Further, the QP values can be adapted at the local level foreach CU using delta QP values sent at the granularity of quantizationgroups.

An Equirectangular projection (“ERP”) format is a common projectionformat used to represent 360-degree videos and images. The projectionmaps meridians to vertical straight lines of constant spacing, andcircles of latitude to horizontal straight lines of constant spacing.Because the particularly simple relationship between the position of animage pixel on the map and its corresponding geographic location onsphere, ERP is one of the most common projections used for 360-degreevideos and images.

Algorithm description of projection format conversion and video qualitymetrics output by JVET gives the introduction and coordinate conversionbetween ERP and sphere. For 2D-to-3D coordinate conversion, given asampling position (m, n), (u, v) can be calculated based on thefollowing equations (1) and (2).

u=(m+0.5)/W,0≤m<W  Eq. (1)

v=(n+0.5)/H,0≤n<H  Eq. (2)

Then, the longitude and latitude (ϕ, θ) in the sphere can be calculatedfrom (u, v) based on the following equations (3) and (4).

ϕ=(u−0.5)×(2×π)  Eq. (3)

θ=(0.5−v)×π  Eq. (4)

Coordinates (X, Y, Z) can be calculated based on the following equations(5)-(7).

X=cos(θ)cos(ϕ)  Eq. (5)

Y=sin(θ)  Eq. (6)

Z=−cos(θ)sin(θ)  Eq. (7)

For 3D-to-2D coordinate conversion starting from (X, Y, Z), (ϕ, θ) canbe calculated based on the following equations (8) and (9). Then, (u, v)is calculated based on equations (3) and (4). Finally, (m, n) can becalculated based on equations (1) and (2).

ϕ=tan⁻¹(−Z/X)  Eq. (8)

θ=sin⁻¹(Y/(X ² +Y ² +Z ²)^(1/2))  Eq. (9)

To reduce the seam artifacts in reconstructed viewports that encompassthe left and right boundaries of the ERP picture, a new format calledpadded equirectangular projection (“PERP”) is provided by paddingsamples on each of the left and the right sides of the ERP picture.

When PERP is used to represent the 360-degree videos, the PERP pictureis encoded. After decoding, the reconstructed PERP is converted back toreconstructed ERP by blending the duplicated samples or cropping thepadded areas.

FIG. 5A shows a schematic of an example blending operation forgenerating reconstructed equirectangular projections, according to someembodiments of the present disclosure. Unless otherwise stated,“recPERP” is used to denote the reconstructed PERP before thepost-processing, and “recERP” is used to denote the reconstructed ERPafter the post-processing. As shown in FIG. 5A, the duplicated samplesof the recPERP can be blended by applying a distance-based weightedaveraging operation. For example, region A can be generated by blendingregions A1 with A2, and region B is generated by blending regions B1with B2.

In the following description, the width and height of unpadded recERPare denoted as “W” and “H” respectively. The left and right paddingwidths are denoted as “P_(L)” and “P_(R)” respectively. The totalpadding width is denoted as “Pw,” which can be a sum of P_(L) and P_(R).In some embodiments, recPERP can be converted to recERP via blendingoperations. For example, for a sample recERP(j,i) in A where i=[0,P_(R−1)] and j=[0, H−1], recERP (j, i) can be determined according tothe following equations.

A=w×A1+(1−w)×A2, where w is from P _(L) /P _(W) to 1  Eq. (10)

recERP(j,i) in A=(recPERP(j,i+P _(L))×(i+P _(L))+recPERP(j,i+P_(L+W))×(P _(R−1))+(P _(W)>>1))/P _(W)  Eq. (11)

In some embodiments, for a sample recERP(j,i) in B where i=[W−P_(L),W−1] and j=[0, H−1], recERP (j,i) can be generated according to thefollowing equations.

B=k×B1+(1−k)×B2, where k is from 0 to P _(L) /P _(W)  Eq. (12)

recERP(j,i) in B=(recPERP(j,i+P _(L))×(P _(R−i) +W)+recPERP(j,i+P_(L−w))×(i−W+P _(L))+(P _(W)>>1))/P _(W)  Eq.(13)

FIG. 5B shows schematic of an example cropping operation for generatingreconstructed equirectangular projections, according to some embodimentsof the present disclosure. As shown in FIG. 5B, during the croppingprocess, the padded samples in recPERP can be directly discarded toobtain recERP. For example, padded samples B1 and A2 can be discarded,and the padded area A is equal to A1 while the padded area B is equal toB2.

In some embodiments, horizontal wrap-around motion compensation can beused to improve the coding performance of ERP. For example, thehorizontal wrap-around motion compensation can be used in the VVCstandard as a 360-specific coding tool designed to improve the visualquality of reconstructed 360-degree video in the ERP format or PERPformat. In a conventional motion compensation, when a motion vectorrefers to samples beyond the picture boundaries of the referencepicture, repetitive padding is applied to derive the values of theout-of-bounds samples by copying from those nearest neighbors on thecorresponding picture boundary. For 360-degree video, this method ofrepetitive padding is not suitable, and could cause visual artefactscalled “seam artefacts” in a reconstructed viewport video. Because a360-degree video is captured on a sphere and inherently has no“boundary,” the reference samples that are out of the boundaries of areference picture in the projected domain can be obtained fromneighboring samples in the spherical domain. For a general projectionformat, it may be difficult to derive the corresponding neighboringsamples in the spherical domain, because it involves 2D-to-3D and3D-to-2D coordinate conversion, as well as sample interpolation forfractional sample positions. This problem can be resolved for the leftand right boundaries of the ERP or PERP projection format, as thespherical neighbors outside of the left picture boundary can be obtainedfrom samples inside the right picture boundary, and vice versa. Giventhe wide usage of the ERP or PERP projection format, and the relativeease of implementation, the horizontal wrap-around motion compensationwas adopted to VVC to improve the visual quality of 360-degree videocoded in the ERP or PERP projection format.

FIG. 6A shows a schematic of an example horizontal wrap-around motioncompensation process for equirectangular projections, according to someembodiments of the present disclosure. As shown in FIG. 6A, when a partof the reference block is outside of the reference picture's left (orright) boundary in the projected domain, instead of repetitive padding,the “out-of-boundary” part can be taken from the corresponding sphericalneighbors that are located within the reference picture toward the right(or left) boundary in the projected domain. In some embodiments,repetitive padding may be used for the top and bottom pictureboundaries.

FIG. 6B shows a schematic of an example horizontal wrap-around motioncompensation process for padded equirectangular projections, accordingto some embodiments of the present disclosure. As shown in FIG. 6B, thehorizontal wrap-around motion compensation can be combined with anon-normative padding method that is often used in 360-degree videocoding. In some embodiments, this is achieved by signaling a high-levelsyntax element to indicate the wrap-around motion compensation offset,which can be set to the ERP picture width before padding. This syntaxcan be used to adjust the position of horizontal wrap-aroundaccordingly. In some embodiments, this syntax is not affected by aspecific amount of padding on the left or right picture boundaries. As aresult, this syntax can naturally support asymmetric padding of the ERPpicture. In the asymmetric padding of the ERP picture, the left andright paddings can be different. In some embodiments, the wrap-aroundmotion compensation can be determined according to the followingequation:

$\begin{matrix}{{{pos}_{x\_}{wrap}} = \left\{ \begin{matrix}{{{pos}_{x} + {offset}};} & {{pos}_{x} < 0} \\{{{pos}_{x} - {offset}};} & {{pos}_{x} > {{picW} - 1}} \\{{pos}_{x};} & {otherwise}\end{matrix} \right.} & {{Eq}.\mspace{11mu}(14)}\end{matrix}$

where the offset can be a wrap-around motion compensation offsetsignaled in the bitstream, picW can be a picture width including thepadding area before encoding, pos_(x) can be a reference positiondetermined by current block position and the motion vector, and theoutput of the equation pos_(x_)wrap can be an actual reference positionwhere the reference block is from in the wrap-around motioncompensation. To save the signaling overhead of the wrap-around motioncompensation offset, it can be in unit of minimum luma coding block,thus the offset can be replaced with offset_(w)×MinCbSizeY whereoffset_(w) is the wrap-around motion compensation offset in unit ofminimum luma coding block which is signaled in the bitstream andMinCbSizeY is the size of minimum luma coding block. In contrast, in atraditional motion compensation, the actual reference position where thereference block is from may be directly derived by clipping pos_(x)within 0 to picW−1.

The horizontal wrap-around motion compensation can provide moremeaningful information for motion compensation when the referencesamples are outside of the reference picture's left and rightboundaries. Under the 360-degree video common test conditions, this toolcan improve compression performance not only in terms ofrate-distortion, but also in terms of reduced seam artefacts andsubjective quality of the reconstructed 360-degree video. The horizontalwrap-around motion compensation can also be used for other single faceprojection formats with constant sampling density in the horizontaldirection, such as adjusted equal-area projection.

In some embodiments, to increase the accuracy of the motion vectors in amerge mode, a bilateral-matching based decoder side motion vectorrefinement (“DMVR”) can be applied. In some embodiments, a merge mode isspecified where motion parameters (e.g., MVs, reference picture indices,reference picture list usage index, etc.) for the current CU areobtained from neighboring CUs, including spatial and temporalcandidates. FIG. 7 shows a schematic of an example bilateral-matchingbased decoding side motion vector refinement, according to someembodiments of the present disclosure. As shown in FIG. 7, inbi-prediction operations, a refined motion vector can be searched aroundan initial motion vector in reference picture list L0 and referencepicture list L1. The bilateral matching method can determine thedistortion between the two candidate blocks in the reference picturelist L0 and reference picture list L1. As shown in FIG. 7, a sum ofabsolute differences (SAD) between the shaded blocks based on eachmotion vector candidate around the initial motion vector can bedetermined. The motion vector candidate with a smaller SAD (e.g.,smallest SAD) can become the refined motion vector that can be used togenerate the bi-predicted signal.

In VVC, the DMVR can be applied for the CUs that are coded with thefollowing modes and features: CU level merge mode with bi-predictionmotion vector; one reference picture is in the past and anotherreference picture is in the future with respect to the current picture;the distances (e.g., difference in picture order count) from tworeference pictures to the current picture are equal; both referencepictures are short-term reference pictures; CU has more than 64 lumasamples; both CU height and CU width are larger than or equal to 8 lumasamples; bi-direction with CU-based weighting (“BCW”) index indicatesequal weight; weighted prediction (“WP”) is not enabled for the currentblock; and combined inter-intra prediction (“CIIP”) mode is not used forthe current block.

In some embodiments, the refined motion vector derived from the DMVRprocess can be used to generate one or more inter prediction samples andalso used in temporal motion vector prediction for coding of futurepictures, while the original motion vector can be used in deblockingprocess and also used in spatial motion vector prediction for coding offuture CU.

In some embodiments, the DMVR process can include a searching scheme.For example, in DMVR, the initial motion vector can be surrounded bysearch points, and the motion vector offset obeys the motion vectordifference mirroring rule. In some embodiments, points that are checkedby the DMVR, denoted by a candidate motion vector pair (MV0, MV1), mayobey the following Equations (15) and (16):

MV0′=MV0+MV_offset  Eq. (15)

MV1′=MV1−MV_offset  Eq. (16)

where MV_offset represents a refinement offset between the initialmotion vector and the refined motion vector in one of the referencepictures. In some embodiments, the refinement search range can be twointeger luma samples from the initial motion vector. In someembodiments, the searching can include the integer sample offset searchstage and fractional sample refinement stage.

In some embodiments, 25-points full search can be applied for integersample offset searching. The SAD of the initial motion vector pair canbe determined first. If the SAD of the initial motion vector pair issmaller than a threshold, the integer sample stage of DMVR can beterminated. If the SAD of the initial motion vector pair is not smallerthan a threshold, SADs of the remaining 24 points can be determined andchecked. In some embodiments, the remaining 24 points can be checked ina raster scanning order. In some embodiments, the point with a smallerSAD (e.g., smallest SAD) can be selected as the output of the integersample offset searching stage. In some embodiments, to reduce thepenalty of the uncertainty in the DMVR refinement, the original motionvector can be favored during the DMVR process. For example, the SADbetween the reference blocks referred by the initial motion vectorcandidates can be decreased by ¼ of the SAD value.

In some embodiments, the integer sample search can be followed by afractional sample refinement. In some embodiments, to reduce thecalculation complexity, the fractional sample refinement can be derivedusing a parametric error surface equation, instead of additionalsearches with an SAD comparison. In some embodiments, the fractionalsample refinement can be conditionally invoked based on the output ofthe integer sample search stage. When the integer sample search stage isterminated with the center having a smaller SAD (e.g., smallest SAD) ineither the first iteration search or the second iteration search, thefractional sample refinement can be further applied.

In some embodiments, in the parametric error surface based sub-pixeloffsets estimation, the center position cost and the costs at fourneighboring positions from the center can be used to fit a 2-D parabolicerror surface equation of the following form:

E(x,y)=A(x−x _(min))² +B(y−y _(min))² +C  Eq. (17)

where (x_(min),y_(min)) corresponds to a fractional position with theleast cost and C corresponds to the minimum cost value. In someembodiments, by solving the above equations using the cost value of thefive search points, the (x_(min),y_(min)) can be determined according tothe following equations:

x _(min)=(E(−1,0)−E(1,0))/(2(E(−1,0)+E(1,0)−2E(0,0)))  Eq. (18)

y _(min)=(E(0,−1)−E(0,1))/(2((E(0,−1)+(E(0,1)−2E(0,0)))  Eq. (19)

In some embodiments, the value of x_(min) and y_(min) can beautomatically constrained to be between −8 and 8 since all cost valuesare positive and the smallest value is E(0,0). This corresponds to ahalf-pel offset with 1/16th-pel motion vector accuracy. The determinedfractional (x_(min), y_(min)) can be added to the integer distancerefinement motion vector to get the refinement delta motion vector withsub-pel precision.

In some embodiments, the motion vectors have a resolution of 1/16 lumasamples. The samples at the fractional position can be interpolatedusing an 8-tap interpolation filter. In DMVR, the search points maysurround the initial fractional-pel motion vector with integer sampleoffset. As a result, the samples of the fractional position may need tobe interpolated for the DMVR search process. In some embodiments, toreduce the calculation complexity, a bi-linear interpolation filter canbe used to generate the fractional samples for the searching process inDMVR. Another important effect is that by using the bi-linearinterpolation filter with a 2-sample search range, the DMVR may not needto access more reference samples compared to a normal motioncompensation process. In some embodiments, after the refined motionvector is determined with the DMVR search process, the normal 8-tapinterpolation filter can be applied to generate the final prediction. Insome embodiments, in order to not access more reference samples than anormal motion compensation process, the samples which are not needed forthe interpolation process based on the original motion vector but neededfor the interpolation process based on the refined motion vector can bepadded from those neighboring samples available in the normal motioncompensation process.

In some embodiments, when the width or the height of a CU is larger than16 luma samples, the CU can be split further into subblocks with a widthor a height equal to 16 luma samples. In some embodiments, the maximumunit size for the DMVR searching process may be limited to 16×16.

Combining the above-described wrap-around motion compensation tool andthe DMVR process can increase coding complexity. For example, when theinput video is a 360-degree video sequence, the wrap-around motioncompensation tool may be enabled in order to improve coding performanceand visual quality. In some embodiments, in VVC (e.g., VVC draft 8),this can be achieved by setting a Picture Parameter Set (“PPS”) flagcalled pps_ref_wraparound_enabled_flag to 1. Then, when coding thecurrent coding unit, if the DMVR conditions are satisfied, a DMVR motionsearch is applied to the current block at the encoder or the decoder tosearch for the refined motion vector. After obtaining the refined motionvector, final prediction samples can be generated with the regular 8-tapinterpolation (or 4-tap for chroma). In some embodiments, if thewrap-around process is enabled, the final motion compensation processcan apply the wraparound offset in order to improve the codingefficiency and the subjective quality.

In VVC (e.g., VVC draft 8), the combination of the wrap-around motioncompensation and the DMVR motion search is allowed. As a result, duringthe DMVR motion search, a more complicated clipping process involving awraparound offset PpsRefWraparoundOffset is applied. This cansignificantly increase the decoder complexity with limited benefits,because the DMVR motion search is applied as an intermediate process inorder to obtain the refined motion vectors.

Embodiments of the present disclosure provide methods to simplify theoperation of DMVR when it is combined with the wrap-around motioncompensation. In some embodiments, when the DMVR is combined with thewrap-around motion compensation, the wrap-around clipping operation isnot performed for the bi-linear interpolation in the DMVR process but isperformed during the final motion compensation process when a regular8-tap motion interpolation filter is used for luma (and 4-tap motioninterpolation is used for chroma). FIG. 8 shows a schematic of anexample decoding side motion vector refinement in combination with awrap-around motion compensation, according to some embodiments of thepresent disclosure. As shown in FIG. 8, steps 602, 604, 606, 608, 610,612, 614, and 616 may be a part of the DMVR process to determine arefined motion vector, and steps 618, 620, 622, 624, 626, 628, and 630may be a part of a final motion compensation process (e.g., when aregular 8-tap motion interpolation filter is used for luma or 4-tapmotion interpolation is used for chroma). As shown in FIG. 8, thesimplification can be achieved by removing steps 604 and 606, which areshown in shaded grey.

In some embodiments, the regular clipping (Clip3 of, for example, step608) and the horizontal wrap-around clipping (ClipH of, for example,step 622) can be defined as follows:

$\begin{matrix}{{{Clip}\; 3\left( {x,y,z} \right)} = \left\{ \begin{matrix}{x;} & {z < x} \\{y;} & {z > y} \\{z;} & {otherwise}\end{matrix} \right.} & {{Eq}.\mspace{11mu}(20)} \\{{{Clip}\;{H\left( {o,W,x} \right)}} = \left\{ \begin{matrix}{{x + o};} & {x < o} \\{{y - o};} & {x > {W - 1}} \\{x;} & {otherwise}\end{matrix} \right.} & {{Eq}.\mspace{11mu}(21)}\end{matrix}$

where “o” is the wraparound offset derived based on a variablePpsRefWraparoundOffset (e.g., a variable in VVC). As shown in Equation20 and Equation 21, the horizontal wrap-around clipping ClipH is a morecomplicated clipping process, and the horizontal wrap-around clippingClipH is dependent on the value of the wraparound offset derived basedon the variable PpsRefWraparoundOffset.

In some embodiments, as shown in FIG. 8, the motion vector searchprocess can be simplified using the regular motion compensation process.In other words, the clipping process based on the wrap-around motioncompensation is not applied. As shown in FIG. 8, steps 604 and 606 referto steps involving the horizontal wrap-around clipping ClipH. Byremoving these steps, the motion vector search process can be simplifiedto improve the overall efficiency in executing the DMVR. In someembodiments, only the final motion prediction process may be performedusing a wrap-around motion compensation, depending on whether thehorizontal wrap-around motion compensation is enabled or not. Thissimplifies the motion vector search process in DMVR not only in terms ofcomputation complexity but also in terms of implementation.

As shown in FIG. 8, in step 602, a first sample position in the searcharea is acquired based on the unrefined motion vector. The sampleposition can skip the wrap-around clipping in steps 604 and 606, andundergoes a full sample position regular clipping clip3 in step 608. Abi-linear interpolation can then be performed in step 610. In step 612,it is determined if the sample is the last sample. If it is determinedthat the sample is not a last sample, step 614 is performed and a nextsample position is acquired. The regular clipping clip3 in step 608 andthe bi-linear interpolation in step 610 can be performed again on thenext sample. If it is determined that the sample is the last sample,step 616 is performed, and the refined motion vector is searched for inthe search area.

As shown in FIG. 8, after step 616, a first sample position in thesubblock is acquired in step 618. Then, it is determined if thehorizontal wrap-around motion compensation is enabled. If the horizontalwrap-around motion compensation is enabled, step 622 is performed, and afull sample position horizontal warp-around clipping clipH is executed.If the horizontal wrap-around motion compensation is not enabled, step624 is performed, and a full sample position regular clipping clip3 isperformed. In some embodiments, the full sample position regularclipping clip3 is executed regardless of whether the horizontalwrap-around motion compensation is enabled. In step 626, a regularinterpolation is performed. In step 628, it is determined if the sampleis the last sample. If the sample is the last sample, the process ends.If the sample is not the last sample, step 630 is performed, and thenext sample position is acquired. Steps 620, 622, 624, 626, or 628 canbe performed again on the next sample position.

In some embodiments, the improved DMVR can be applied on VVC bymodifying the semantics being used in VVC (e.g., VVC draft 8). Forexample, to simplify the operation of DMVR when it is combined with thewrap-around motion compensation, the wrap-around clipping operation forthe bilinear interpolation in the DMVR process is not performed,regardless of the value of variable pps_ref_wraparound_enabled_flag(e.g., in VVC). FIG. 9 shows semantics of an example improved fractionalsample bilinear interpolation process, according to some embodiments ofthe present disclosure. As shown in FIG. 9, changes from the VVC areshown in italic, and with proposed deleted semantics being further shownin strikethrough. As shown in FIG. 9, all italicized texts are instrikethroughs.

In some embodiments, as shown in FIG. 9, variable “refPicIsScaled”indicating whether the selected reference picture requires scaling mayno longer be needed as an input to the fractional sample bilinearinterpolation process.

In some embodiments, as shown in FIG. 9, variablerefWraparoundEnabledFlag may no longer be needed to be set to(pps_wraparound_enabled_flag && !refPicIsScaled), since variablerefPicIsScaled may no longer be available as an input to the fractionalsample bilinear interpolation process.

In some embodiments, as shown in FIG. 9, variablerefWraparoundEnabledFlag may no longer be needed as an input into theluma sample bilinear interpolation process.

In some embodiments, as shown in FIG. 9, variable xInt_(i) in the lumasample bilinear interpolation process can be determined regardless ofthe value in variable refWraparoundEnabledFlag, since variablerefWraparoundEnabledFlag may no longer be available as an input to theluma sample bilinear interpolation process. In some embodiments,function Clip3 shown in FIG. 9 can be applied as Equation (20).

Embodiments of the present disclosure further methods for performingDMVR processes. FIG. 10 shows a flowchart of an example decoding sidemotion vector refinement in combination with a wrap-around motioncompensation, according to some embodiments of the present disclosure.In some embodiments, method 10000 shown in FIG. 10 can be performed byapparatus 400 shown in FIG. 4. In some embodiments, method 10000 shownin FIG. 10 can be executed according to the semantics shown in FIG. 9.In some embodiments, method 10000 shown in FIG. 10 includes a DMVRprocess performed according to the VVC standard. In some embodiments,method 10000 shown in FIG. 10 can be performed with a 360-degree videosequence as input.

In step S10010, a refined motion vector for a target coding unit isdetermined without using wrap-around motion compensation. In someembodiments, the refined motion vector is searched around an initialmotion vector in one or more reference picture lists. For example, asshown in FIG. 7, the refined motion vector can be searched inbi-prediction operations around an initial motion vector in referencepicture list L0 and reference picture list L1. In some embodiments, themotion vector candidate with a lower SAD (e.g., lowest SAD) can becomethe refined motion vector.

In some embodiments, in step S10010, a non-wraparound clipping operationcan be performed. For example, as shown in FIG. 8, a regular clippingoperation Clip3 can be performed as a part of the process to determinethe refined motion vector. The regular clipping operation Clip3 is anon-wraparound clipping operation. Moreover, a horizontal wrap-aroundclipping operation ClipH is not performed as a part of the process todetermine the refined motion vector.

In some embodiments, in step S10010, a fractional sample can begenerated using a bi-linear interpolation filter. In some embodiments,the fractional sample is generated without a wrap-around operation. Forexample, as shown in FIG. 9, a bilinear interpolation process can beconducted without variables associated with a wrap-around operation(e.g., refWraparoundEnabledFlag, pps_ref_wraparound_enabled_flag,PpsRefWraparoundOffset, etc.). In some embodiments, as shown in FIG. 7,the fractional sample is generated as a part of the fractional samplerefinement. Further, the fractional sample refinement can beconditionally invoked based on the output of the integer sample searchstage. In some embodiments, to reduce the calculation complexity, thefractional sample refinement can be derived using a parametric errorsurface equation, instead of additional searches with an SAD comparison.

In some embodiments, in step S10010, the refined motion vector can bedetermined without a VVC standard scaling variable as input. Forexample, as shown the semantics of FIG. 9, variable “refPicIsScaled”indicating whether the selected reference picture requires scaling mayno longer be needed as an input to the fractional sample bilinearinterpolation process.

In step S10020, it is determined whether the sequence wrap-around motioncompensation flag is enabled. For example, as shown in step 620 of FIG.8, it is determined if a horizontal wrap-around motion compensation isenabled. In some embodiments, the determination is conducted outside ofthe determination for the refined motion vector. For example, as shownin FIG. 8, step 620 is conducted after step 616, which determines therefined motion vector.

In step S10030, a bi-predicted signal is generated using the wrap-aroundmotion compensation in response to a determination that the wrap-aroundmotion compensation is enabled. In some embodiments, the bi-predictedsignal is one of a luma signal or a chroma signal. In some embodiments,the refined motion vector is used to generate one or more interprediction samples and used in temporal motion vector prediction. Forexample, as shown in FIG. 7, the refined motion vector derived from theDMVR process can be used to generate one or more inter predictionsamples and also used in temporal motion vector prediction for futurepicture coding.

In some embodiments, a non-transitory computer-readable storage mediumincluding instructions is also provided, and the instructions may beexecuted by a device (such as the disclosed encoder and decoder), forperforming the above-described methods. Common forms of non-transitorymedia include, for example, a floppy disk, a flexible disk, hard disk,solid state drive, magnetic tape, or any other magnetic data storagemedium, a CD-ROM, any other optical data storage medium, any physicalmedium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROMor any other flash memory, NVRAM, a cache, a register, any other memorychip or cartridge, and networked versions of the same. The device mayinclude one or more processors (CPUs), an input/output interface, anetwork interface, and/or a memory.

It should be noted that, the relational terms herein such as “first” and“second” are used only to differentiate an entity or operation fromanother entity or operation, and do not require or imply any actualrelationship or sequence between these entities or operations. Moreover,the words “comprising,” “having,” “containing,” and “including,” andother similar forms are intended to be equivalent in meaning and be openended in that an item or items following any one of these words is notmeant to be an exhaustive listing of such item or items, or meant to belimited to only the listed item or items.

As used herein, unless specifically stated otherwise, the term “or”encompasses all possible combinations, except where infeasible. Forexample, if it is stated that a database may include A or B, then,unless specifically stated otherwise or infeasible, the database mayinclude A, or B, or A and B. As a second example, if it is stated that adatabase may include A, B, or C, then, unless specifically statedotherwise or infeasible, the database may include A, or B, or C, or Aand B, or A and C, or B and C, or A and B and C.

It is appreciated that the above described embodiments can beimplemented by hardware, or software (program codes), or a combinationof hardware and software. If implemented by software, it may be storedin the above-described computer-readable media. The software, whenexecuted by the processor can perform the disclosed methods. Thecomputing units and other functional units described in this disclosurecan be implemented by hardware, or software, or a combination ofhardware and software. One of ordinary skill in the art will alsounderstand that multiple ones of the above described modules/units maybe combined as one module/unit, and each of the above describedmodules/units may be further divided into a plurality ofsub-modules/sub-units.

In the foregoing specification, embodiments have been described withreference to numerous specific details that can vary from implementationto implementation. Certain adaptations and modifications of thedescribed embodiments can be made. Other embodiments can be apparent tothose skilled in the art from consideration of the specification andpractice of the invention disclosed herein. It is intended that thespecification and examples be considered as exemplary only, with a truescope and spirit of the invention being indicated by the followingclaims. It is also intended that the sequence of steps shown in figuresare only for illustrative purposes and are not intended to be limited toany particular sequence of steps. As such, those skilled in the art canappreciate that these steps can be performed in a different order whileimplementing the same method.

The embodiments may further be described using the following clauses:

1. A video data processing method, comprising:

performing a decoder side motion vector refinement (DMVR) process togenerate a bi-predicted signal, wherein performing the DMVR processcomprises:

-   -   determining a refined motion vector for a target coding unit,        without using wrap-around motion compensation;    -   determining whether the wrap-around motion compensation is        enabled; and    -   in response to a determination that the wrap-around motion        compensation is enabled, generating, based on the refined motion        vector, a bi-predicted signal using the wrap-around motion        compensation.

2. The method of clause 1, wherein the bi-predicted signal is one of aluma signal or a chroma signal.

3. The method of any one of clauses 1 and 2, wherein determining therefined motion vector for the target coding unit, without using thewrap-around motion compensation comprises:

performing a non-wraparound clipping operation; and

generating a fractional sample using a bi-linear interpolation filter.

4. The method of any one of clauses 1-3, wherein the DMVR process isperformed according to versatile video coding standard.

5. The method of clause 4, wherein the DMVR process is performed withouta versatile video coding standard scaling variable as input, wherein thescaling variable indicates whether a selected reference picture in theDMVR process requires scaling.

6. The method of any one of clauses 1-5, wherein the video processingmethod is performed with a 360-degree video sequence as input.

7. The method of any one of clauses 1-6, wherein the refined motionvector is used to generate one or more inter prediction samples and usedin a temporal motion vector prediction for future pictures encoding.

8. A system for performing video data processing, the system comprising:

a memory storing a set of instructions; and

a processor configured to execute the set of instructions to cause thesystem to perform:

-   -   performing a decoder side motion vector refinement (DMVR)        process to generate a bi-predicted signal, wherein performing        the DMVR process comprises.        -   determining a refined motion vector for a target coding            unit, without using wrap-around motion compensation;        -   determining whether the wrap-around motion compensation is            enabled; and        -   in response to a determination that the wrap-around motion            compensation is enabled, generating, based on the refined            motion vector, a bi-predicted signal using the wrap-around            motion compensation.

9. The system of clause 8, wherein the bi-predicted signal is one of aluma signal or a chroma signal.

10. The system of any one of clauses 8 or 9, wherein the processor isfurther configured to execute the set of instructions to cause thesystem to perform:

performing a non-wraparound clipping operation; and

generating a fractional sample using a bi-linear interpolation filter.

11. The system of any one of clauses 8-10, wherein the DMVR process isperformed according to versatile video coding standard.

12. The system of clause 11, wherein the DMVR process is performedwithout a versatile video coding standard scaling variable as input,wherein the scaling variable indicates whether a selected referencepicture in the DMVR process requires scaling.

13. The system of any one of clauses 8-12, wherein the video processingmethod is performed with a 360-degree video sequence as input.

14. The system of any one of clauses 8-13, wherein the refined motionvector is used to generate one or more inter prediction samples and usedin a temporal motion vector prediction for future pictures encoding.

15. A non-transitory computer readable medium that stores a set ofinstructions that is executable by one or more processors of anapparatus to cause the apparatus to initiate a method for performingvideo data processing, the method comprising:

performing a decoder side motion vector refinement (DMVR) process togenerate a bi-predicted signal, wherein performing the DMVR processcomprises:

-   -   determining a refined motion vector for a target coding unit,        without using wrap-around motion compensation;    -   determining whether the wrap-around motion compensation is        enabled; and    -   in response to a determination that the wrap-around motion        compensation is enabled, generating, based on the refined motion        vector, a bi-predicted signal using the wrap-around motion        compensation.

16. The non-transitory computer readable medium of clause 15, whereinthe bi-predicted signal is one of a luma signal or a chroma signal.

17. The non-transitory computer readable medium of any one of clauses 15or 16, wherein the set of instructions is executable by the at least oneprocessor of the computer system to cause the computer system to furtherperform:

performing a non-wraparound clipping operation; and

generating a fractional sample using a bi-linear interpolation filter.

18. The non-transitory computer readable medium of any one of clauses15-17, wherein the DMVR process is performed according to versatilevideo coding standard.

19. The non-transitory computer readable medium of clause 18, whereinthe DMVR process is performed without a versatile video coding standardscaling variable as input, wherein the scaling variable indicateswhether a selected reference picture in the DMVR process requiresscaling.

20. The non-transitory computer readable medium of any one of clauses15-19, wherein the video processing is performed with a 360-degree videosequence as input.

21. The non-transitory computer readable medium of any one of clauses15-20, wherein the refined motion vector is used to generate one or moreinter prediction samples and used in a temporal motion vector predictionfor future pictures encoding.

In the drawings and specification, there have been disclosed exemplaryembodiments. However, many variations and modifications can be made tothese embodiments. Accordingly, although specific terms are employed,they are used in a generic and descriptive sense only and not forpurposes of limitation.

What is claimed is:
 1. A video data processing method, comprising:performing a decoder side motion vector refinement (DMVR) process togenerate a bi-predicted signal, wherein performing the DMVR processcomprises: determining a refined motion vector for a target coding unit,without using wrap-around motion compensation; determining whether thewrap-around motion compensation is enabled; and in response to adetermination that the wrap-around motion compensation is enabled,generating, based on the refined motion vector, a bi-predicted signalusing the wrap-around motion compensation.
 2. The method of claim 1,wherein the bi-predicted signal is one of a luma signal or a chromasignal.
 3. The method claim 1, wherein determining the refined motionvector for the target coding unit, without using the wrap-around motioncompensation comprises: performing a non-wraparound clipping operation;and generating a fractional sample using a bi-linear interpolationfilter.
 4. The method of claim 1, wherein the DMVR process is performedaccording to versatile video coding standard.
 5. The method of claim 4,wherein the DMVR process is performed without a versatile video codingstandard scaling variable as input, wherein the scaling variableindicates whether a selected reference picture in the DMVR processrequires scaling.
 6. The method of claim 1, wherein the video processingmethod is performed with a 360-degree video sequence as input.
 7. Themethod of claim 1, wherein the refined motion vector is used to generateone or more inter prediction samples and used in a temporal motionvector prediction for future pictures encoding.
 8. A system forperforming video data processing, the system comprising: a memorystoring a set of instructions; and a processor configured to execute theset of instructions to cause the system to perform: performing a decoderside motion vector refinement (DMVR) process to generate a bi-predictedsignal, wherein performing the DMVR process comprises: determining arefined motion vector for a target coding unit, without usingwrap-around motion compensation; determining whether the wrap-aroundmotion compensation is enabled; and in response to a determination thatthe wrap-around motion compensation is enabled, generating, based on therefined motion vector, a bi-predicted signal using the wrap-aroundmotion compensation.
 9. The system of claim 8, wherein the bi-predictedsignal is one of a luma signal or a chroma signal.
 10. The system ofclaim 8, wherein the processor is further configured to execute the setof instructions to cause the system to perform: performing anon-wraparound clipping operation; and generating a fractional sampleusing a bi-linear interpolation filter.
 11. The system of claim 8,wherein the DMVR process is performed according to versatile videocoding standard.
 12. The system of claim 11, wherein the DMVR process isperformed without a versatile video coding standard scaling variable asinput, wherein the scaling variable indicates whether a selectedreference picture in the DMVR process requires scaling.
 13. The systemof claim 8, wherein the video processing method is performed with a360-degree video sequence as input.
 14. The system of claim 8, whereinthe refined motion vector is used to generate one or more interprediction samples and used in a temporal motion vector prediction forfuture pictures encoding.
 15. A non-transitory computer readable mediumthat stores a set of instructions that is executable by one or moreprocessors of an apparatus to cause the apparatus to initiate a methodfor performing video data processing, the method comprising: performinga decoder side motion vector refinement (DMVR) process to generate abi-predicted signal, wherein performing the DMVR process comprises:determining a refined motion vector for a target coding unit, withoutusing wrap-around motion compensation; determining whether thewrap-around motion compensation is enabled; and in response to adetermination that the wrap-around motion compensation is enabled,generating, based on the refined motion vector, a bi-predicted signalusing the wrap-around motion compensation.
 16. The non-transitorycomputer readable medium of claim 15, wherein the bi-predicted signal isone of a luma signal or a chroma signal.
 17. The non-transitory computerreadable medium of claim 15, wherein the set of instructions isexecutable by the at least one processor of the computer system to causethe computer system to further perform: performing a non-wraparoundclipping operation; and generating a fractional sample using a bi-linearinterpolation filter.
 18. The non-transitory computer readable medium ofclaim 15, wherein the DMVR process is performed according to versatilevideo coding standard.
 19. The non-transitory computer readable mediumof claim 18, wherein the DMVR process is performed without a versatilevideo coding standard scaling variable as input, wherein the scalingvariable indicates whether a selected reference picture in the DMVRprocess requires scaling.
 20. The non-transitory computer readablemedium of claim 15, wherein the video processing is performed with a360-degree video sequence as input.